Deep Learning Investigation for Turbulent Flows
Dnr:
NAISS 2023/22-1326
Type:
NAISS Small Compute
Principal Investigator:
Kin Wing Wong
Affiliation:
Kungliga Tekniska högskolan
Start Date:
2024-01-16
End Date:
2024-10-01
Primary Classification:
20306: Fluid Mechanics and Acoustics
Allocation
- Centre Storage at NSC: 500 GiB
- Tetralith at NSC: 10 x 1000 core-h/month
Abstract
This request for the computing allocation is for a master thesis project that will be commenced in Jan 2024. The work is focused on generation of 3D turbulent flow data with passive scalar based on DNS using foam-extend. The generated data will be tested with the NIF data approximation framework to achieve both dimensionality reduction and the exploration of integrating NIF for super-resoution of turbluent flow data.